Both cognitive computing and artificial intelligence are part of the next big supercomputing developments. However, the two terms are different. Artificial intelligence (AI) is concerned with results – simulating how humans would make a decision. Cognitive computing is concerned with the process – how humans think and reason. Cognitive computing doesn’t make the final decision, the human does.
The origins of the distinction
IBM first drew the line between cognitive computing and artificial intelligence while developing supercomputers such as Deep Blue and Watson.
Deep Blue beat world chess champion Gary Kasparov because of raw computing power, not human-style reasoning. It could analyze millions of chess positions per second and calculate the consequences 20 moves into the future. That decision-making was pure result-driven AI, not the process-driven thinking behind cognitive computing.
For example, IBM used AI to beat two long-time champions on the game show Jeopardy. IBM’s Watson is now being used for many purposes including making medical diagnoses. In a classic example, a doctor was given a case study of a cancer patient. With Watson’s help, the doctor could review and rank treatment options such as chemotherapy for effectiveness, speed, and convenience. The AI approach would be for Watson to make the decision for the doctor. The cognitive computing approach works differently: the doctor interacts with Watson for guidance, then makes the final call alone. IBM also calls it “insights-as-a-service” and “platforms-as-a-service.”
Background
Alan Turing first raised the idea of artificial intelligence in 1950 with his “Turing Test.” The test is simple: a human evaluator reads a conversation between a person and a computer. If the evaluator can’t reliably tell which one is the machine, the machine passes as intelligent. The test itself is result-oriented, which fits the same pattern. The Turing Archive defines it as “the science of making computers do things that require intelligence when done by humans.”
The key difference is one of approach
According to Brian Krzanich, CEO of Intel, cognitive computing systems use thinking, reasoning, and remembering (human approaches) to solve problems. Cognitive computing lets systems “learn and adapt as new data arrives,” as well as explore the way humans do. AI tests what humans can accomplish.
Artificial intelligence, says Peter Norvig, Director of Research at Google, “decides what actions to take and when to take them.” AI is when supercomputers solve problems that would take real intelligence for a person, rather than a simple reflex.
According to IBM, “cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally.” Cognitive science is about getting the computer to simulate how a person would reason through the same problem.
Practical Applications
Both artificial intelligence and cognitive computing are being used in a variety of fields including
- Medicine and healthcare
- Information management
- Analysis of data
- Finance
- General security and cybersecurity
- Consumer applications
- Face recognition technology such as that used in Google Photos
- Driverless cars
Cognitive computing analyzes huge amounts of data from every connected device, including the Internet of Things (IoT).
To learn more about cognitive computing, please contact a professional data center for answers
Cognitive computing and artificial intelligence are continuing developments that are helping to tackle many human problems. These approaches require huge amounts of data, as well as large quantities of processing power. To learn how your company can benefit, ask to speak with one of our knowledgeable IT consultants.
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